docs: def predict(self, p, x):
          """
          Parameters
          ----------
          p: ndarray
              (Ns, d) array of predictor variables (Ns samples, d dimensions)
              for regression
          x: ndarray
              ndarray of (x, y) points. Needs to be a (Ns, 2) array
              corresponding to the lon/lat, for example.
              array of Points, (x, y, z) pairs of shape (N, 3) for 3d kriging
  
          Returns
          -------
          pred: ndarray
              The expected value of ys for the query inputs, of shape (Ns,).
  
          """
  
          return self.krige_residual(x) + self.regression_model.predict(p)